247 Background: Recently, a 30-day all-cause readmission rate has been proposed as a measure of quality of care. Readmissions are assumed to reflect failure by the discharging physician, hospital, or post acute care. These rates are generally easily calculated from available administrative data, and classifiable as "related to the previous discharge diagnosis" or not. Present on admission modifiers may enhance classification and assignment to "preventable" or "non-preventable," "expected or non-expected." This methodology is not generally applicable to the oncology population. The experience with one major cancer center is presented as an example of the limitations of such an approach. Methods: We analyzed 52,097 oncology admissions in an all-payer population that occurred between January 2010 and January 2012. Results: A mean of 32.5% (n=16,918) were readmitted within 30 days, compared to a "peer" group in the database of the University Health Consortium, median of 15%. The attached graph demonstrates the stability of this proportion. Leukemia, lymphoma, stem cell patients (46%), all patients with intense medical needs and frequent readmissions, n=7,635, were the largest subgroup. 42% (n=7,099) were readmissions for chemotherapy or immunotherapy, both planned and expected, and 11% (n=1,803) due to neutropenic fever, pneumonia, or sepsis, all common in this population and neither unexpected nor usually preventable. The most preventable, unexpected, and unplanned readmissions were for postoperative infection, dehydration, and urinary tract infection, accounting for 3.6% (n=609). Thus, the majority of readmissions were planned, expected, or not preventable. Conclusions: In a cancer population at an academic cancer hospital, the majority of readmission are not only planned, but also expected for this population of patients and should not be construed as representative of a quality of care issue. Proper stratification and classification of readmissions is essential to the interpretation of such a measure.
Objective National guidelines recommend prophylactic anticoagulation for all hospitalized patients with cancer to prevent hospital-acquired venous thromboembolism (VTE). However, adherence to these evidence-based recommended practice patterns remains low. We performed a quality improvement project to increase VTE pharmacologic prophylaxis rates among patients with gynecologic malignancies hospitalized for nonsurgical indications and evaluated the resulting effect on rates of development of VTE. Methods/materials In June 2011, departmental VTE practice guidelines were implemented for patients with gynecologic malignancies who were hospitalized for nonsurgical indications. A standardized VTE prophylaxis module was added to the admission electronic order sets. Outcome measures included: number of admissions receiving VTE pharmacologic prophylaxis within 24 hours of admission; and number of potentially preventable hospital-acquired VTEs diagnosed within 30 and 90 days of discharge. Outcomes were compared between a pre-guideline implementation cohort (N=99), a post-guideline implementation cohort (N=127), and a sustainability cohort assessed 2 years after implementation (N=109). Patients were excluded if upon admission they had a VTE, were considered low risk for VTE, or had a documented contraindication to pharmacologic prophylaxis. Results Administration of pharmacologic prophylaxis within 24 hours of admission increased from 20.8% to 88.2% immediately following the implementation of guidelines, but declined to 71.8% in our sustainability cohort (p<0.001). There was no difference in VTE incidence among the three cohorts (n=2 (4.2%) v. n=3 (3.9%) v. n=3 (4.2%), respectively; p=1.00). Conclusions Our quality improvement project improved pharmacologic VTE prophylaxis rates. A small decrease in prophylaxis over the subsequent 2 years suggests a need for continued surveillance to optimize quality improvement initiatives. Despite increased adherence to guidelines, VTE rates did not decline in this high-risk population.
189 Background: Pneumonia is the major cause of death due to infectious diseases in the United States. In the cancer patient, pneumonia is the overall leading infectious cause of death. Pneumonia Core Measures (PCM) and Clinical Pathways are frequently used by healthcare organizations to ensure the delivery of high-quality care and pathogen-directed therapy. A multidisciplinary team was organized at the University of Texas MD Anderson Cancer Center (MDACC) Emergency Center (EC) into a Pneumonia Team to optimize care and to enhance compliance with current PCM. Methods: A retrospective review of EC patients during pneumonia season was completed. Results: Three areas for improvement in the EC were identified. The areas include lack of EC staff’s knowledge on PCM, lack of standardized order-sets for pathogen-directed treatment, and cancer patients presenting with pneumonia syndromes that fall outside established Community-Acquired Pneumonia (CAP) guidelines. The identified problems were addressed through three strategies: Intense EC staff education initially and yearly prior to pneumonia season (September-March). Microbiologic analysis of the pathogens responsible for the pneumonias in our unique cancer population at MDACC. Development and implementation of an institutional pneumonia algorithm and an order-set. The Pneumonia Team also identified a gap between our patient population and the current PCM. Pneumonia patients at MDACC EC are divided into two distinct groups, solid tumor and hematologic cancers. The microbiology analyzed in both groups is consistent with Healthcare-Associated Pneumonia (HCAP) and not CAP. Microbiology analysis identified gram positive, gram negative, fungal, viral and multi-drug resistant organisms. The initial analysis demonstrated that 87% of our patients met criteria for HCAP and only 12% met CAP. Based on this percentage, antibiotic selection for our CAP patients comprises a small portion of our total population. Conclusions: Our current algorithm and order-set optimize care and minimize variation to match our patient population. These findings provide important considerations for policy makers in regard to pneumonia measurements in a cancer setting.
42 Background: As part of the Affordable Care Act (ACA) of 2010, the Prospective Payment System-Exempt Cancer Hospital Quality Reporting (PCHQR) Program was created for 11 cancer centers. PCHQR includes an initial set of 5 measures mandated for federal reporting and expanded to include 18 measures for subsequent program years. The Alliance of Dedicated Cancer Centers (ADCC) formed in 1983 to include and represent the interests of the same 11 centers. As a small and previously organized group, we have been able to collaborate closely throughout implementation of PCHQR to understand, evaluate, and offer feedback on the program. Methods: The ADCC began sharing and reviewing data on mandated measures upon the release of the ACA in 2010. Numerator and denominator data for measures are manually uploaded from each center to a common master file bi-annually. In December 2013, ADCC hospitals formally began sharing feedback on concordant and non-concordant cases through email, bi-annual in person meetings, and monthly teleconferences. Results: Through sharing feedback on data submission with each other, CMS, and CMS contractors the ADCC learned the following lessons: 1- Limitations exist in the submission of our current data sets, (e.g. inability to accurately capture all scenarios that lead to appropriate delays in treatment). 2- Process of care measures are topped out with aggregated values above 95% for multiple consecutive quarters. 3- 4 of the existing measures and multiple forthcoming measures have case selection criteria creating sample sizes of little comparative value or statistical significance. 4- Tertiary care centers share many unique treatment patterns affecting compliance (e.g. lag time from referral to diagnosis, high percentage of patients on clinical trials). 5- Subject matter experts embedded at the 11 centers are critical for measure development/ refinement (e.g. Tumor Registrars, ICP’s). 6- CMS, CMS contractors, and affected hospitals must establish effective communication channels. Conclusions: Our early experiences indicate it is challenging to apply broad national measures to the ADCC hospitals. The 11 centers seek to continually improve upon this mandate and advance clinical practices.
123 Background: Heart failure (HF) is a clinical problem of emerging importance in cancer care. The advances in cancer detection and complex treatment regimens have resulted in increased cancer treatment induced HF. The literature indicates that more than 50% of all patients exposed to anthracyclines will show some degree of cardiac dysfunction either acutely or 10 to 20 years after treatment, and 5% of those patients will develop overt HF. Successful management requires a collaborative, interdisciplinary approach. The purpose of this presentation is to discuss how the “Heart Success Program” (HSP) resulted in cost effective and clinical quality outcomes in patients with cancer and HF. Methods: The HSP was piloted in the emergency center and telemetry units with high volume admission of HF patients. The HSP includes comprehensive education of patients, families, and health care providers regarding HF management in cancer patients. HSP implementation includes a HF order set, patient education booklet, and educational videotape specific for patients with cancer and HF. Weekly interdisciplinary clinical rounds provide a forum for discussion of identified patient’s problems and formulation of solutions. Endpoint outcomes include compliance with the Center for Medicare and Medicaid Services (CMS) core measures for HF, as well as decreasing HF readmissions. Results: The pilot implementation of the HSP resulted in decreased hospital length of stay by 57%, and average hospital admission cost by 60%. Despite multiple co morbid conditions, patients were discharged with improved functional status and compliance with CMS HF core measures. Conclusions: The findings from this quality improvement project showed significant impact in clinical and cost outcomes for patients with cancer and HF. The multidisciplinary team approach that provided support to patients and their families and allowed for patients to continue their cancer treatment resulting in improved outcomes. As we move toward value-based purchasing, the HSP provides an example of how collaboration and standardized process improvement impacts cost and quality in the oncology population.
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